The Covid election

Over at MoneyIllusion, I did a post discussing some odd election anomalies. Now that I’ve had a chance to look at the detailed election map more closely, certain consistent trends seem to show up.

Let’s start with the basic overview. In 2016, Clinton beat Trump by 2.9 million in the popular vote. In 2020, Biden won by over 7 million votes. So obviously the country shifted substantially toward the Democrats.

But many sub-groups went the other way:

1. Vietnamese-American areas in Orange County shifted dramatically toward Trump, by margins on the order of 40%
2. Working class Asian neighborhoods shifted strongly toward Trump.
3. Hispanic areas shifted strongly toward Trump. (But still Democratic.)
4. In Rockland County, New York, Orthodox Jewish areas shifted strongly toward Trump, with margins not usually seen outside Turkmenistan.
5. While data is sketchy, Amish areas in Pennsylvania seemed to shift substantially toward Trump.
6. African-American areas shifted mildly toward Trump (remaining strongly Democratic in absolute terms.)

I’ve found news articles discussing most of these shifts, and in almost every case the article mentioned resentment against Covid shutdowns.

So if all these groups shifted toward Trump, many quite strongly, how did Biden do so much better than Clinton?

It wasn’t rural white voters.  That was a mixed bag, with no clear trend toward the Democrats. So where did the extra 4.1 million Democratic margin come from?

The detailed election map of vote shifts from 2016 is clear. Look at almost any urban area and you see the same pattern. Red for Hispanic areas (sharp shift to Trump.) Pink for African American areas (mild shift to Trump.) And blue for white suburban areas, (strong shift to Biden.)

All across America, white suburban areas shifted toward the Democrats.

These were often well-educated white-collar workers who worked from home during Covid. Whereas working class minorities resented Covid restrictions, these voters resented the fact that Trump didn’t seem to make much effort to control Covid, discouraging testing, pushing unproven remedies, ridiculing mask wearers, etc.

This might be the first election where the voters who did well under a president turned against him while those that suffered economically turned toward him.

In this post, I’m not taking a stand as to which voters were right, just trying to understand why some parts of the country swung one way while others moved in the opposite direction.

Here’s a map of the vote shift in Philadelphia area, which is typical. The bright red in the north side is Hispanic. The pink area just to the west is mostly black, and the further out areas are mostly white suburbs.  Again, these are vote shifts.  In absolute terms Trump still did fairly well among whites and poorly among minorities.

PS.  You may wish to compare these vote patterns to the racial dot map of America, which is quite informative.  I’m sure people will do regression analyses, but these vote shifts are so obvious you don’t even need to run regressions.

PPS.  I certainly don’t mean to suggest Covid was the only issue.  Various news articles suggest that communities such as Vietnamese-Americans and Orthodox Jews were also motivated by other issues.

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A Review of Minimum Wage Effects

From Alan Manning, in Journal of Economic Perspectives (a journal of the American Economic Association), “The Elusive Employment Effect of the Minimum Wage”: Conclusion Much of the literature on the employment of the minimum wage focuses on the question of  “what is the employment effect of the minimum wage” using an empirical specification in  which […]

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The anti-science presidency?

…recent Congressional Budget Office estimates suggest that with the already enacted $900 billion package — but without any new stimulus — the gap between actual and potential output will decline from about $50 billion a month at the beginning of the year to $20 billion a month at its end. The proposed stimulus will total in […]

The post The anti-science presidency? appeared first on Marginal REVOLUTION.

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Cost/Benefit Analysis or Rock, Paper, Scissors

President Reagan began regulatory reform with Executive Order 12291, titled simply “Federal Regulation”; President Clinton watered it down with EO 12866; and President Trump beefed it up with EO 13771 (“Reducing Regulation and Controlling Regulatory Costs”) and EO 13777 (“Enforcing the Regulatory Reform Agenda.”) The executive orders required a cost/benefit analysis to assure that the costs of major regulations would be compared with their benefits. But on his first day in office, President Biden revoked those executive orders with his own memorandum titled “Modernizing Regulatory Review.” If you read the memorandum carefully, you’ll see that the word “modernizing” is inapt. Indeed, the memorandum would more accurately be labeled “Replacing Cost/Benefit Analysis with Rock, Paper, Scissors.”

This is from David R. Henderson, “Open Season For New Regulations,” Defining Ideas, February 4, 2021.

Another excerpt:

But even if that weren’t a problem, there are two other major problems. First, notice that the OMB is being put in a position not so much to screen regulations as to propose them. Does this mean the agencies will quit proposing regulations and passively await direction from the OMB? No way. Indeed, the memorandum reads as if President Biden is proposing that OMB be a cheerleader for new regulation. He states that he wants OIRA to “play a more proactive role in partnering with agencies to explore, promote, and undertake regulatory initiatives that are likely to yield significant benefits.” Rah, rah, sis boom bah.

The second major problem is one that anyone with much experience dealing with bureaucracy will probably notice: with so many possible criteria, regulators will have running room to implement regulations they like because those regulations pass some criteria even while they fail others. The regulators might, for example, choose a regulation that promotes public health and safety but at the expense of economic growth. Without cost/benefit analysis as a guide, how will they trade off between these two criteria? Any way they like.

Note also the disappointment I express with Cass Sunstein’s take. He should know better.

Read the whole thing.

 

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Thursday assorted links

1. One of these people is an abysmal reasoner.  Kudos to you if you can avoid those more general fallacies across a broader range of settings. 2. “I find that following the introduction of ride-sharing services in a city, individuals decrease their student debt balance and probability of default.” 3. James Brown concert Paris 1968, […]

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